README.md

metadata

tags:
  - sklearn
  - regression
  - sales-forecast
  - RandomForest
library_name: sklearn
metrics:
  - rmse
  - r2
model-index:
  - name: RandomForest
    results:
      - task:
          type: tabular-regression
          name: Sales Forecasting
        dataset:
          name: SuperKart Data
          type: tabular
        metrics:
          - type: rmse
            value: 280.8543593979435
          - type: r2
            value: 0.9308695977150697

SuperKart Sales Prediction Model

Model Description

This is a RandomForest model trained to predict sales revenue (Product_Store_Sales_Total) for SuperKart stores. It utilizes a Scikit-Learn Pipeline that handles:

1. Preprocessing: OneHotEncoding for categorical variables and Scaling for numerical variables.
2. Modeling: The best performing regressor selected from Random Forest, Gradient Boosting, and XGBoost.

Performance

• RMSE: 280.8544
• R2 Score: 0.9309
• MAE: 114.7186

Usage

This model expects a pandas DataFrame with the same columns as the training set (Product_Weight, Product_Sugar_Content, etc.).